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Software Engineer Data Infrastructure Jobs in California

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Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$126K - $165K/yr

They are seeking an experienced Data Infrastructure Engineer to enhance their AI data infrastructure by building tools and software components for managing robot data and cloud resources.

Figure

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$126K - $165K/yr

They are seeking an experienced Data Infrastructure Engineer to enhance their AI data ... Responsibilities : • Design, build, and maintain tools and software components that offload ...

Figure

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$126K - $165K/yr

They are seeking an experienced Data Infrastructure Engineer to enhance their AI data infrastructure by building tools and software components for managing robot data and cloud resources.

Figure

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$126K - $165K/yr

They are seeking an experienced Data Infrastructure Engineer to enhance their AI data infrastructure by building tools and software components for managing robot data and cloud resources.

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Showing results 21-40

All JobsSoftware Engineer Data Infrastructure JobsSoftware Engineer Data Infrastructure Jobs in California

Software Engineer Data Infrastructure information

See California salary details

$43.9K

$128K

$175.2K

How much do software engineer data infrastructure jobs pay per year?

As of Aug 11, 2026, the average yearly pay for software engineer data infrastructure in California is $128,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $135,700.00 per year, depending on experience, location, and employer.

How does a software engineer data infrastructure typically collaborate with data scientists and other engineering teams?

As a Software Engineer in Data Infrastructure, you'll frequently work alongside data scientists, analysts, and other engineering teams to ensure that data pipelines and storage systems are reliable, scalable, and efficient. Collaboration often involves translating data requirements into technical solutions, troubleshooting data flow issues, and optimizing infrastructure for both performance and cost. Regular meetings, code reviews, and cross-functional planning sessions are common, allowing you to gain insights from various perspectives and ensure the infrastructure meets the evolving needs of the organization.

What is the difference between Software Engineer Data Infrastructure vs Data Engineer?

AspectSoftware Engineer Data InfrastructureData Engineer
Required CredentialsBachelor's in CS or related, often with certifications in cloud or data toolsBachelor's in CS, Data Science, or related; similar certifications
Work EnvironmentDevelops and maintains data infrastructure, collaborates with data teamsBuilds data pipelines, manages data storage and processing systems
Employer & Industry UsageTech companies, data-driven organizations, cloud providersFinance, healthcare, tech firms, any industry with large data needs
Common Search & ComparisonYesYes

Software Engineer Data Infrastructure and Data Engineer roles often overlap in skills and work environment, focusing on building and maintaining data systems. However, Software Engineers Data Infrastructure tend to focus more on the underlying infrastructure and integration, while Data Engineers emphasize data pipeline development and data management. Both roles are essential in data-driven organizations and require similar credentials and industry usage.

What is a software engineer data infrastructure?

Software Engineer Data Infrastructure are professionals who design, build, and maintain the underlying systems and tools that enable organizations to collect, store, process, and analyze large volumes of data efficiently. They work on creating scalable data pipelines, managing databases, and ensuring data reliability and security. Their work supports data scientists, analysts, and business teams by providing robust, high-performance infrastructure for all data-related operations.

What are the key skills and qualifications needed to thrive as a software engineer data infrastructure, and why are they important?

To thrive as a Software Engineer Data Infrastructure, you need strong programming skills (such as Python, Java, or Scala), a solid understanding of distributed systems, and experience with data modeling and storage solutions, often backed by a degree in computer science or a related field. Familiarity with technologies like Hadoop, Spark, Kafka, SQL/NoSQL databases, and cloud platforms, as well as certifications in cloud or big data, are highly valued. Excellent problem-solving abilities, collaboration, and clear communication distinguish top performers in this role. These skills ensure robust, scalable, and reliable data infrastructure that supports organizational analytics and business goals.
What are popular job titles related to Software Engineer Data Infrastructure jobs in California? For Software Engineer Data Infrastructure jobs in California, the most frequently searched job titles are:
What job categories do people searching Software Engineer Data Infrastructure jobs in California look for? The top searched job categories for Software Engineer Data Infrastructure jobs in California are:
Software Engineer Data Infrastructure jobs near you
Infographic showing various Software Engineer Data Infrastructure job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 2% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $128,018 per year, or $61.5 per hour.

Senior Software Engineer - Data Infrastructure

Applied Intuition

Sunnyvale, CA • On-site

$143K - $188K/yr

Full-time

Re-posted 14 days ago

Job description

Job Summary:
Applied Intuition is powering the future of physical AI, creating the digital infrastructure needed for intelligent machines. The role involves scaling open-source data infrastructure and working across the data lifecycle to support various business units with high-quality software development.
Responsibilities:
• Scale infrastructure to support all deployment types (cloud, hybrid, on-prem) and across regions
• Be involved in the end to end data lifecycle, from the external-facing product to the underlying platform and infrastructure for it
• Build features to tune processing pipeline for fast data ingestion and indexing depending on customer's needs and workloads
• Enable product workflows that expose performant query interfaces and offer easy-to-use integration hooks
• Develop and deploy high-quality software using modern tooling and frameworks, especially open-source technologies
Qualifications:
Required:
• A Bachelor's degree in Computer Science, Software Engineering, or equivalent
• 3+ years of professional experience
• Experience with large-scale open source data technologies (Spark, Kafka, Hudi, Flyte, etc.)
• Experience with containerization and other modern software development workflows
• Knowledge of the open source landscape with judgment on when to choose open source versus build in-house
Preferred:
• Expertise with modern programming languages (Python, C++, GoLang, Scala, etc.)
• Experience with other open-source data technologies not listed above
• Expertise with Kubernetes
• Experience with enterprise software, including on-prem and/or cloud environments
• Deep knowledge of data quality, data profiling and cleansing techniques
Company:
Applied Intuition provides software infrastructure to safely develop, test, and deploy autonomous vehicles
 at scale. Founded in 2017, the company is headquartered in Mountain View, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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